Unlocking Mass Mobile Video Analytics with Advanced Neural Memory Networks

该项目将开发神经记忆架构和密集时空束调整，以预测运动，行为，并在大型异步视频源中执行多传感器融合。这种能力将使我们能够更好地询问和分析大量的视频信息记录从大量的智能手机，运动相机，和监控摄像头存在于感兴趣的公共事件。其成果包括将多个视频输入摄取到密集和动态的3D重建中，以进行知识表示和发现，以及通过新的时空分析方法分析事件和行为。这将为视频取证分析、警务和应急响应提供重大好处。

This project will develop neural memory architectures and dense spatial-temporal bundle adjustment to predict movement, behaviour, and perform multi-sensor fusion across large asynchronous video feeds. This capability will allow us to better interrogate and analyse mass video information recorded from the vast number of smartphones, action cameras, and surveillance cameras which exist at public events of interest. Outcomes include the ability to ingest multiple video feeds into a dense and dynamic 3D reconstruction for knowledge representation and discovery, and analysis of events and behaviour through new spatio-temporal analytic approaches. This will offer significant benefits for video forensic analysis, policing, and emergency response.